Validation of a machine learning algorithm for identifying infants at risk of hypoxic ischaemic encephalopathy in a large unseen data set
In a large unseen data set an open-source algorithm could identify infants at risk of HIE in the immediate postnatal period. This may aid focused clinical examination, transfer to tertiary care (if necessary) and timely intervention.
Authors
- Deirdre M. Murray (ORCID: https://orcid.org/0000-0002-2201-9912)
- Daragh O’Boyle (ORCID: https://orcid.org/0000-0002-6960-4334)
- Anne L. Murray (ORCID: https://orcid.org/0009-0008-3548-3969)
- Brian H. Walsh (ORCID: https://orcid.org/0000-0003-4665-6884)
Institutions
- University College Cork (IE)
- Cork University Hospital (IE)
Publication Details
- Journal
- Archives of Disease in Childhood Fetal & Neonatal
- Published
- 2024-09-09
- DOI
- https://doi.org/10.1136/archdischild-2024-327366
- Citations
- 10
- Primary Topic
- Neonatal and fetal brain pathology
- Type
- article
- Field-Weighted Citation Impact
- 11.09